Role of weak ties in link prediction of complex networks
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
Towards time-aware link prediction in evolving social networks
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Boosting social network connectivity with link revival
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Learning algorithms for link prediction based on chance constraints
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Temporal Link Prediction Using Matrix and Tensor Factorizations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Time aware index for link prediction in social networks
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Link prediction via matrix factorization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Who will follow you back?: reciprocal relationship prediction
Proceedings of the 20th ACM international conference on Information and knowledge management
Temporal link prediction by integrating content and structure information
Proceedings of the 20th ACM international conference on Information and knowledge management
When will it happen?: relationship prediction in heterogeneous information networks
Proceedings of the fifth ACM international conference on Web search and data mining
Reciprocal and heterogeneous link prediction in social networks
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Back-buy prediction based on TriFG
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Feature selection for link prediction
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Proceedings of the 21st ACM international conference on Information and knowledge management
A survey on proximity measures for social networks
Search Computing
ALIVE: a multi-relational link prediction environment for the healthcare domain
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
Coauthor prediction for junior researchers
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Link Prediction: Fair and Effective Evaluation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Organizational overlap on social networks and its applications
Proceedings of the 22nd international conference on World Wide Web
sonLP: social network link prediction by principal component regression
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Learning to predict reciprocity and triadic closure in social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Inferring anchor links across multiple heterogeneous social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proximity measures for link prediction based on temporal events
Expert Systems with Applications: An International Journal
Prediction in a microblog hybrid network using bonacich potential
Proceedings of the 7th ACM international conference on Web search and data mining
Internal link prediction: A new approach for predicting links in bipartite graphs
Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
| Hi-index | 0.00 |
One of the core tasks in social network analysis is to predict the formation of links (i.e. various types of relationships) over time. Previous research has generally represented the social network in the form of a graph and has leveraged topological and semantic measures of similarity between two nodes to evaluate the probability of link formation. Here we introduce a novel local probabilistic graphical model method that can scale to large graphs to estimate the joint co-occurrence probability of two nodes. Such a probability measure captures information that is not captured by either topological measures or measures of semantic similarity, which are the dominant measures used for link prediction. We demonstrate the effectiveness of the co-occurrence probability feature by using it both in isolation and in combination with other topological and semantic features for predicting co-authorship collaborations on three real datasets.